CN117288099B - Machine vision-based aluminum-plastic composite board production quality detection and analysis method - Google Patents
Machine vision-based aluminum-plastic composite board production quality detection and analysis method Download PDFInfo
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- 239000002131 composite material Substances 0.000 title claims abstract description 290
- 238000004519 manufacturing process Methods 0.000 title claims abstract description 55
- 238000001514 detection method Methods 0.000 title claims abstract description 50
- 238000004458 analytical method Methods 0.000 title claims abstract description 37
- 239000011248 coating agent Substances 0.000 claims description 119
- 238000000576 coating method Methods 0.000 claims description 119
- AZDRQVAHHNSJOQ-UHFFFAOYSA-N alumane Chemical group [AlH3] AZDRQVAHHNSJOQ-UHFFFAOYSA-N 0.000 claims description 69
- 238000013461 design Methods 0.000 claims description 57
- 238000000034 method Methods 0.000 claims description 41
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 claims description 29
- 229910052782 aluminium Inorganic materials 0.000 claims description 29
- 238000013441 quality evaluation Methods 0.000 claims description 29
- 230000010354 integration Effects 0.000 claims description 26
- 238000011156 evaluation Methods 0.000 claims description 18
- 238000004364 calculation method Methods 0.000 claims description 13
- 238000005520 cutting process Methods 0.000 claims description 12
- 238000007639 printing Methods 0.000 claims description 9
- 238000005286 illumination Methods 0.000 claims description 8
- 238000012216 screening Methods 0.000 claims description 7
- 239000000853 adhesive Substances 0.000 claims description 3
- 230000001070 adhesive effect Effects 0.000 claims description 3
- 230000005540 biological transmission Effects 0.000 claims description 3
- 238000007499 fusion processing Methods 0.000 claims description 3
- 238000002347 injection Methods 0.000 claims description 3
- 239000007924 injection Substances 0.000 claims description 3
- 238000007781 pre-processing Methods 0.000 claims description 3
- 238000012545 processing Methods 0.000 claims description 3
- 238000003860 storage Methods 0.000 claims description 3
- 239000007921 spray Substances 0.000 description 10
- 238000003475 lamination Methods 0.000 description 7
- 238000007405 data analysis Methods 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 238000003908 quality control method Methods 0.000 description 4
- 230000007547 defect Effects 0.000 description 3
- 239000010410 layer Substances 0.000 description 3
- 238000005507 spraying Methods 0.000 description 3
- 238000007796 conventional method Methods 0.000 description 2
- 238000010030 laminating Methods 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 229910000838 Al alloy Inorganic materials 0.000 description 1
- 230000002159 abnormal effect Effects 0.000 description 1
- 238000007792 addition Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013329 compounding Methods 0.000 description 1
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- 238000010586 diagram Methods 0.000 description 1
- 238000006073 displacement reaction Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000000465 moulding Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 239000002344 surface layer Substances 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
- G01B11/06—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness for measuring thickness ; e.g. of sheet material
- G01B11/0608—Height gauges
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/26—Measuring arrangements characterised by the use of optical techniques for measuring angles or tapers; for testing the alignment of axes
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/30—Measuring arrangements characterised by the use of optical techniques for measuring roughness or irregularity of surfaces
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/01—Arrangements or apparatus for facilitating the optical investigation
- G01N21/13—Moving of cuvettes or solid samples to or from the investigating station
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
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Abstract
The invention relates to the technical field of composite board production quality detection, in particular to a machine vision-based aluminum-plastic composite board production quality detection analysis method.
Description
Technical Field
The invention relates to the technical field of composite board production quality detection, in particular to a machine vision-based aluminum-plastic composite board production quality detection analysis method.
Background
The aluminum-plastic composite board is a material formed by compounding aluminum alloy and plastic, and is widely applied to the fields of buildings, billboards, transportation tools and the like. However, quality problems are easy to occur in the production process of the aluminum-plastic composite board due to the production process, improper operation, material quality and the like, so that the appearance and the performance of the aluminum-plastic composite board are affected, and the safety and the service life of a building are also affected. Therefore, the method has important significance in quality detection in the production process of the aluminum-plastic composite board.
With the continuous development of machine vision technology, the machine vision-based aluminum-plastic composite board production quality detection method is widely applied gradually, and although the existing requirements can be met, certain limitations still exist, and the method is specifically expressed in the following steps: the existing aluminum-plastic composite board production quality detection method mainly focuses on appearance size and surface layer quality detection of coating spraying, and on one hand, careful consideration of an internal aluminum core structure of the aluminum-plastic composite board is omitted. In fact, abnormal changes and integration degree of the aluminum core structure directly influence the attaching tightness of the aluminum plate and the plastic plate in the aluminum-plastic composite plate and even the supporting strength of the whole structure, the integration quality of the aluminum core structure is a key factor for guaranteeing the quality of the aluminum-plastic composite plate, and the existing production quality detection method lacks a detection step for the key factor, so that the reliability of a detection result is not high.
On the other hand, there is a limit to analyzing the coating spray quality only by coating spray color consistency. First, color, while it may be a consideration for the color design of the coating, cannot be a consideration for the uniformity of the coating spray. Second, a single coating spray quality cannot represent the overall coating quality. Although the aluminum core integration quality reaches the standard, the surface coating of the aluminum layer can be uneven due to other factors. The existing method has less consideration or insufficient analysis strength in the aspect, so that the existing aluminum-plastic composite board production quality detection is insufficient in evaluation of the whole coating quality, and the attractiveness and quality of the building are further affected.
Disclosure of Invention
In order to overcome the defects in the background technology, the embodiment of the invention provides a machine vision-based aluminum-plastic composite board production quality detection analysis method, which can effectively solve the problems related to the background technology.
The aim of the invention can be achieved by the following technical scheme: the machine vision-based aluminum-plastic composite board production quality detection and analysis method comprises the following steps: s1, conveying a composite board production quality detection area: and transmitting the produced target aluminum-plastic composite board to a production quality detection area through a transmission belt, wherein the production quality detection area comprises a first detection area, a second detection area and a third detection area.
S2, detecting the quality of the basic design of the composite board: and scanning edge line segments of the target aluminum-plastic composite board through a line scanning camera for detecting a first area, constructing a three-dimensional basic frame model of the target aluminum-plastic composite board, judging whether basic design quality of the target aluminum-plastic composite board meets the standard, if so, continuously transmitting the target aluminum-plastic composite board to a second detection area and executing S3, otherwise, printing a first-level unqualified label on the target aluminum-plastic composite board and executing S6.
S3, detecting the integration quality of the aluminum core of the composite board: and (3) scanning the inside of the target aluminum-plastic composite board through a laser scanning instrument for detecting the second area, constructing an internal aluminum core three-dimensional structure model of the target aluminum-plastic composite board, judging whether the aluminum core integration quality of the target aluminum-plastic composite board meets the standard, if so, continuously transmitting the target aluminum-plastic composite board to the third area to be detected and executing S4, otherwise, printing a second-level unqualified label on the target aluminum-plastic composite board and executing S6.
S4, detecting the adhesion quality of the composite board coating: and (3) respectively carrying out image acquisition on the surface coating of the target aluminum-plastic composite board under the same angle and different illumination conditions by using the high-definition camera for detecting the three areas, judging whether the coating adhesion quality of the target aluminum-plastic composite board meets the standard, if so, executing S5, otherwise, printing three-level unqualified labels on the target aluminum-plastic composite board and executing S6.
S5, conveying a qualified production area of the composite board: and transmitting the target aluminum-plastic composite plate to a production qualified area.
S6, conveying the unqualified areas of composite board production: and transmitting the target aluminum-plastic composite plate to a production failure area.
Preferably, the determining whether the basic design quality of the target aluminum-plastic composite panel meets the standard includes: importing a three-dimensional basic frame model of the target aluminum-plastic composite board into software to obtain basic dimension parameters including length, width and height, comparing the basic dimension parameters with design dimension parameters of the target aluminum-plastic composite board stored in a WEB cloud to obtain dimension deviation values of the length, width and height of the target aluminum-plastic composite board, and respectively recording the dimension deviation values asCalculating the size design conformity of the target aluminum-plastic composite plate>，Wherein->The length, the width and the height of the design size parameters of the target aluminum-plastic composite board.
The three-dimensional basic frame model of the target aluminum-plastic composite board is provided with a set number of planes, each plane is regarded as a rectangle, two base edges and two high edges exist, a pair of base edges and high edges with adjacent relation in the planes are marked as adjacent groups of edges, a pair of base edges or high edges with opposite relation in the planes are marked as opposite groups of edges, the parallelism of each opposite group of edges and the perpendicularity of each adjacent group of edges in each plane of the target aluminum-plastic composite board are obtained and respectively marked asWherein->Numbering the planes of the target aluminum-plastic composite board, < >>，/>Numbering the opposite edges in the plane, < >>，/>Numbering the adjacent groups of edges in the plane, < >>Calculating the basic cutting conformity of the target aluminum-plastic composite board>，Wherein->Is natural constant (18)>The number of the aluminum-plastic composite plates is the target number of the planes of the aluminum-plastic composite plates.
Preferably, the method for obtaining the parallelism of each opposite group of edges and the perpendicularity of each adjacent group of edges in each plane of the target aluminum-plastic composite plate comprises the following steps: acquiring the relative angles of each relative group of edges and each adjacent group of edges in each plane of the target aluminum-plastic composite board through an angle measuring tool in software with a three-dimensional size analysis functionBy the formula->Obtaining the parallelism of each opposite group edge in each plane of the target aluminum-plastic composite board, and obtaining the parallelism of each opposite group edge in each plane of the target aluminum-plastic composite board by the formula +.>And obtaining the perpendicularity of each adjacent group of edges in each plane of the target aluminum-plastic composite board.
Preferably, whether the basic design quality of the target aluminum-plastic composite board meets the standard or not is judged, and the method further comprises: calculating basic design quality evaluation coefficient of target aluminum-plastic composite board，/>Wherein->Respectively obtaining a weight ratio corresponding to the preset size design conformity and the basic cutting conformity, and reasonably threshold value of basic design quality evaluation coefficient and preset basic design quality evaluation coefficient of the target aluminum-plastic composite board>Comparing, if->And judging that the basic design quality of the target aluminum-plastic composite plate meets the standard, and otherwise, judging that the basic design quality of the target aluminum-plastic composite plate does not meet the standard.
Preferably, the determining whether the aluminum core integration quality of the target aluminum-plastic composite board meets the standard comprises: extracting a standard internal aluminum core three-dimensional structure model of a target aluminum-plastic composite board stored in a WEB cloud, recognizing the aluminum core of the target aluminum-plastic composite board as an egg-supporting conical structure, and acquiring contact distances between left and right endpoints of each egg-supporting structure and an aluminum plate in the internal aluminum core three-dimensional structure model of the target aluminum-plastic composite board, wherein the contact distances are respectively recorded asWherein->Numbering the egg tray structure>Analyzing the fitting degree evaluation coefficient between each egg support structure of the target aluminum-plastic composite board and the aluminum plate +.>The calculation formula is as follows:wherein->Is a reasonable deviation threshold value of the contact distance between the left end point and the right end point of the preset egg tray structure and the aluminum plate, < +.>For a reasonable threshold value of the contact distance between a preset egg-shaped support structure end point and an aluminum plate, further calculating an overall fit degree evaluation coefficient between an aluminum core of the target aluminum-plastic composite plate and the aluminum plate +.>，Wherein->A reasonable threshold value of a coefficient is evaluated for the degree of fit between a preset aluminum core egg support structure and an aluminum plate, and the degree of fit is ∈10>The aluminum core of the aluminum-plastic composite board is the target +.>Evaluation coefficient of the degree of adhesion between the individual egg-carrier structure and the aluminum plate, < >>The number of the egg trays is the number of the egg trays.
Obtaining the attaching distance between the bottom surface of each egg support structure and the plastic plate in the internal aluminum core three-dimensional structure model of the target aluminum-plastic composite plateAnalyzing an overall adhesion degree evaluation coefficient between an aluminum core and a plastic plate of a target aluminum-plastic composite plate +.>。
Preferably, whether the aluminum core integration quality of the target aluminum-plastic composite board meets the standard or not is judged, and the method further comprises the following steps: aluminum core integration quality evaluation coefficient of analysis target aluminum-plastic composite boardThe calculation formula is as follows: />Integrating the composite board with a preset composite board aluminum core to obtain a reasonable quality evaluation coefficient threshold value +.>Comparing, if->And (5) judging that the aluminum core integration quality of the target aluminum-plastic composite board meets the standard, and otherwise, judging that the aluminum core integration quality of the target aluminum-plastic composite board does not meet the standard.
Preferably, the determining whether the coating adhesion quality of the target aluminum-plastic composite panel meets the standard includes: and recording each surface coating image of the target aluminum-plastic composite board acquired under the same angle and different illumination conditions as each appointed image, obtaining a coating integrated image through image fusion processing, and converting the coating integrated image into an RGB color space after preprocessing to obtain the intensity value of each pixel point in the coating integrated image in a R, G, B color channel.
Extracting a coating design color of the WEB cloud storage target aluminum-plastic composite board, analyzing an intensity value of a R, G, B color channel corresponding to the color, constructing a chromaticity three-dimensional coordinate system by taking R, G, B color channel intensity as a coordinate axis, obtaining coordinates of each pixel point in a coating integrated image and the coating design color, and calculating coordinate distances between each pixel point in the image and the coating design colorWherein->For coating the number of each pixel in the integrated image, < >>。
Dividing the region of the coating integrated image to obtain each image subarea, and calculating the gray average value of each image subareaWherein->For the numbering of the sub-areas of the respective image>。
The coating injection quality evaluation coefficient of the analysis target aluminum-plastic composite board is calculated by the following formula:wherein->For the number of image subregions>And designing a coordinate distance limiting threshold value of the color for the pixel point in the preset image and the coating.
Preferably, the determining whether the coating adhesion quality of the target aluminum-plastic composite panel meets the standard includes: aiming at each appointed image, each suspected raised area and each suspected recessed area in each appointed image are obtained through the set pixel threshold range and the connected domain searching processing, each actual raised area and each actual recessed area of the target aluminum-plastic composite board surface coating are further screened out by utilizing the recessed shadow fluctuation characteristics and the raised high light fluctuation characteristics, the corresponding areas and the corresponding depths are obtained and are respectively recorded asWherein->For the number of the actual raised areas +.>，/>For the number of the actual recessed areas +.>The flatness of the surface coating of the target aluminum-plastic composite panel is analyzed, and the calculation formula is as follows: />Wherein->The surface coating area of the aluminum-plastic composite board is a preset target.
Preferably, the screening process of each actual convex area and each actual concave area of the surface coating of the target aluminum-plastic composite panel is as follows: and acquiring a highlight value of each suspected convex region and a shadow value of each suspected concave region in each appointed image, taking the position of the region center unit pixel circle domain as a base point, screening each convex region and each concave region with the same position of the region center unit pixel circle domain in each appointed image, and respectively marking the convex region and the concave region as each preliminary selected convex region and each preliminary selected concave region.
And checking the highlight value of each primary selection convex area in each designated image and the shadow value of each primary selection concave area in each designated image, and obtaining the highlight fluctuation factor of each primary selection convex area and the shadow fluctuation factor of each primary selection concave area.
If the high-light-wave factor of a certain primary selected bulge area is smaller than the set value, the primary selected bulge area is indicated to be an actual bulge area, and then each actual bulge area of the surface coating of the target aluminum-plastic composite plate is obtained, and each actual concave area of the surface coating of the target aluminum-plastic composite plate is obtained in a similar manner.
Preferably, the method for judging whether the coating adhesion quality of the target aluminum-plastic composite board meets the standard further comprises: analysis target aluminum-plastic composite board coating adhesion quality standard coefficientThe calculation formula is as follows: />The adhesive quality evaluation coefficient of the composite board coating is reasonably threshold value +.>Comparing, if->And judging that the coating adhesion quality of the target aluminum-plastic composite plate reaches the standard, and otherwise, judging that the coating adhesion quality does not reach the standard.
Compared with the prior art, the embodiment of the invention has at least the following advantages or beneficial effects: (1) According to the invention, the dimensional design conformity and basic cutting conformity of the target aluminum-plastic composite board are combined, the basic design quality evaluation coefficient of the target aluminum-plastic composite board is comprehensively analyzed, and the control strictness and accuracy of the target aluminum-plastic composite board in the production cutting process are effectively ensured from basic dimensional parameters, parallelism among line segments and verticality, so that the problems of inconsistent size or uneven cutting of the target aluminum-plastic composite board are timely found.
(2) According to the invention, by constructing the three-dimensional structure model of the inner aluminum core of the target aluminum-plastic composite board and aiming at the egg-support type conical structure of the three-dimensional structure model, the aluminum core integration quality evaluation coefficient of the target aluminum-plastic composite board is analyzed from two angles of the lamination degree evaluation coefficients among each egg-support structure of the aluminum core of the target aluminum-plastic composite board, the defect that the conventional method is insufficient or insufficient in consideration of the layer is overcome, the supporting strength and the tight lamination degree of the aluminum core structure in the target aluminum-plastic composite board are effectively known, the production quality control process of the aluminum-plastic composite board is further optimized, the production efficiency is improved, and the production cost is reduced.
(3) According to the invention, the difference between the spray color and the design color of the coating in the target aluminum-plastic composite board coating integrated image is analyzed in the form of the coordinate distance, the matching degree of the coating color and the design color is quantitatively evaluated, the color precision and consistency of the product are ensured, the gray average deviation among all subareas in the target aluminum-plastic composite board coating integrated image is used for carefully knowing the spray uniformity of the coating, and thus the spray quality of the coating is more accurately evaluated.
(4) According to the invention, by utilizing concave shadow fluctuation characteristics and convex high light fluctuation characteristics under different illumination conditions of the same shooting angle, each actual convex area and each actual concave area of the surface coating of the target aluminum-plastic composite plate are reasonably screened, so that the accuracy and scientificity of data analysis are ensured to a great extent, and further, the higher credibility of the data analysis result is ensured.
(5) According to the invention, through analyzing the coating spraying quality evaluation coefficient and the flatness of the surface coating of the target aluminum-plastic composite board, the coating adhesion quality evaluation coefficient of the target aluminum-plastic composite board is comprehensively considered, so that each aspect of the coating can be accurately, comprehensively and deeply known, the attractiveness, the durability and the service life of the aluminum-plastic composite board are ensured, and the requirements of various practical applications are met.
(6) According to the invention, the first-stage, second-stage and third-stage unqualified labels are printed on the target aluminum-plastic composite board, so that unqualified products can be conveniently tracked and traced, the reasons for quality problems can be better analyzed, and quality maintenance and control can be more quickly performed, thereby improving quality control efficiency.
Drawings
The invention will be further described with reference to the accompanying drawings, in which embodiments do not constitute any limitation of the invention, and other drawings can be obtained by one of ordinary skill in the art without inventive effort from the following drawings.
FIG. 1 is a schematic flow chart of the method of the present invention.
Fig. 2 is a schematic side structural view of the target aluminum-plastic composite panel of the present invention.
Fig. 3 is a schematic diagram of a reference structure of the target aluminum-plastic composite panel according to the present invention.
Reference numerals: 1. a coating; 2. an aluminum plate; 3. egg-supporting type conical aluminum core; 4. and (5) molding the plate.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, 2 and 3, the invention provides a machine vision-based aluminum-plastic composite board production quality detection and analysis method, which comprises the following steps: s1, conveying a composite board production quality detection area: and transmitting the produced target aluminum-plastic composite board to a production quality detection area through a transmission belt, wherein the production quality detection area comprises a first detection area, a second detection area and a third detection area.
S2, detecting the quality of the basic design of the composite board: and scanning edge line segments of the target aluminum-plastic composite board through a line scanning camera for detecting a first area, constructing a three-dimensional basic frame model of the target aluminum-plastic composite board, judging whether basic design quality of the target aluminum-plastic composite board meets the standard, if so, continuously transmitting the target aluminum-plastic composite board to a second detection area and executing S3, otherwise, printing a first-level unqualified label on the target aluminum-plastic composite board and executing S6.
Specifically, whether the basic design quality of the target aluminum-plastic composite board meets the standard or not is judged, and the method comprises the following steps: importing a three-dimensional basic frame model of a target aluminum-plastic composite board into software with a three-dimensional size analysis function, acquiring basic size parameters including length, width and height, comparing the basic size parameters with design size parameters of the target aluminum-plastic composite board stored in a WEB cloud, and obtaining size deviation values of the length, the width and the height of the target aluminum-plastic composite board, wherein the size deviation values are respectively recorded asCalculating the size design conformity of the target aluminum-plastic composite plate>，/>Wherein->The length, the width and the height of the design size parameters of the target aluminum-plastic composite board.
It should be noted that the software may be CAD software, and the basic dimension parameter may be obtained by a length measuring tool in the software.
The three-dimensional basic frame model of the target aluminum-plastic composite board is provided with a set number of planes, each plane is regarded as a rectangle, two base edges and two high edges exist, a pair of base edges and high edges with adjacent relation in the planes are marked as adjacent groups of edges, a pair of base edges or high edges with opposite relation in the planes are marked as opposite groups of edges, the parallelism of each opposite group of edges and the perpendicularity of each adjacent group of edges in each plane of the target aluminum-plastic composite board are obtained and respectively marked asWherein->Is the target aluminum plastic compositeNumbering of the planes of the plywood->，/>Numbering the opposite edges in the plane, < >>，/>Numbering the adjacent groups of edges in the plane, < >>Calculating the basic cutting conformity of the target aluminum-plastic composite board>，Wherein->Is natural constant (18)>The number of the aluminum-plastic composite plates is the target number of the planes of the aluminum-plastic composite plates.
It should be noted that, the base side in the rectangle generally refers to a long side, and the high side generally refers to a short side, if the rectangle is a square, a certain line segment in the plane may be arbitrarily selected as the base side, the adjacent side is the high side, and the opposite side is the other base side.
Specifically, the method for obtaining the parallelism of each opposite group of edges and the perpendicularity of each adjacent group of edges in each plane of the target aluminum-plastic composite plate comprises the following steps: acquiring the relative angles of each relative group of edges and each adjacent group of edges in each plane of the target aluminum-plastic composite board through an angle measuring tool in software with a three-dimensional size analysis functionBy the formula->Obtaining the parallelism of each opposite group edge in each plane of the target aluminum-plastic composite board, and obtaining the parallelism of each opposite group edge in each plane of the target aluminum-plastic composite board by the formula +.>And obtaining the perpendicularity of each adjacent group of edges in each plane of the target aluminum-plastic composite board.
Specifically, whether the basic design quality of the target aluminum-plastic composite board meets the standard or not is judged, and the method further comprises the following steps: calculating basic design quality evaluation coefficient of target aluminum-plastic composite board，/>Wherein->Respectively obtaining a weight ratio corresponding to the preset size design conformity and the basic cutting conformity, and reasonably threshold value of basic design quality evaluation coefficient and preset basic design quality evaluation coefficient of the target aluminum-plastic composite board>Comparing, if->And judging that the basic design quality of the target aluminum-plastic composite plate meets the standard, and otherwise, judging that the basic design quality of the target aluminum-plastic composite plate does not meet the standard.
According to the embodiment of the invention, the dimensional design conformity and the basic cutting conformity of the target aluminum-plastic composite board are combined, the basic design quality evaluation coefficient of the target aluminum-plastic composite board is comprehensively analyzed, and the control strictness and accuracy of the target aluminum-plastic composite board in the production cutting process are effectively ensured from basic dimensional parameters, the parallelism and the verticality among line segments, so that the problems of inconsistent size or uneven cutting of the target aluminum-plastic composite board are timely found.
S3, detecting the integration quality of the aluminum core of the composite board: and (3) scanning the inside of the target aluminum-plastic composite board through a laser scanning instrument for detecting the second area, constructing an internal aluminum core three-dimensional structure model of the target aluminum-plastic composite board, judging whether the aluminum core integration quality of the target aluminum-plastic composite board meets the standard, if so, continuously transmitting the target aluminum-plastic composite board to the third area to be detected and executing S4, otherwise, printing a second-level unqualified label on the target aluminum-plastic composite board and executing S6.
Specifically, whether the aluminum core integration quality of the target aluminum-plastic composite board meets the standard or not is judged, and the method comprises the following steps: extracting a standard internal aluminum core three-dimensional structure model of a target aluminum-plastic composite board stored in a WEB cloud, recognizing the aluminum core of the target aluminum-plastic composite board as an egg-supporting conical structure, and acquiring contact distances between left and right endpoints of each egg-supporting structure and an aluminum plate in the internal aluminum core three-dimensional structure model of the target aluminum-plastic composite board, wherein the contact distances are respectively recorded asWherein->Numbering the egg tray structure>Analyzing the fitting degree evaluation coefficient between each egg support structure of the target aluminum-plastic composite board and the aluminum plate +.>The calculation formula is as follows:wherein->Is a reasonable deviation threshold value of the contact distance between the left end point and the right end point of the preset egg tray structure and the aluminum plate, < +.>For a reasonable threshold value of the contact distance between a preset egg-shaped support structure end point and an aluminum plate, further calculating an overall fit degree evaluation coefficient between an aluminum core of the target aluminum-plastic composite plate and the aluminum plate +.>，Wherein->A reasonable threshold value of a coefficient is evaluated for the degree of fit between a preset aluminum core egg support structure and an aluminum plate, and the degree of fit is ∈10>The aluminum core of the aluminum-plastic composite board is the target +.>Evaluation coefficient of the degree of adhesion between the individual egg-carrier structure and the aluminum plate, < >>The number of the egg trays is the number of the egg trays.
The identification method of the left and right end points of the egg tray structure is as follows: the base edge of the aluminum plate surface plane of the target aluminum-plastic composite plate is taken as a direction axis, any direction of the base edge of the aluminum plate surface plane is taken as a positive direction, an end point of the egg support structure, which is more deviated to one side in the positive direction, is considered as a right end point, and the rest end points are considered as left end points.
Obtaining the attaching distance between the bottom surface of each egg support structure and the plastic plate in the internal aluminum core three-dimensional structure model of the target aluminum-plastic composite plateAnalyzing an overall adhesion degree evaluation coefficient between an aluminum core and a plastic plate of a target aluminum-plastic composite plate +.>。
The finite element analysis tool in the software can be used for performing stress analysis, displacement analysis and the like on the model, so that the contact distance between the left end point and the right end point of each egg support structure and the aluminum plate and the bonding distance between the bottom surface of each egg support structure and the plastic plate are calculated. For example, in ANSYS, a "contact" command may be used to set up a contact pair and analyzed to obtain a contact distance.
It should be further noted that the analysis process of the overall lamination degree evaluation coefficient between the aluminum core and the plastic plate of the target aluminum-plastic composite plate is as follows: analysis target evaluation coefficient of lamination degree between each aluminum core supporting structure and plastic plate of aluminum-plastic composite plateThe calculation formula is as follows: />Wherein->For a reasonable threshold value of the laminating distance between the bottom surface of the preset aluminum core egg tray structure and the plastic plate, further calculating an overall laminating degree evaluation coefficient between the aluminum core of the target aluminum-plastic composite plate and the plastic plate，/>Wherein->And evaluating a coefficient reasonable threshold value for the lamination degree between a preset aluminum core egg tray structure and the plastic plate.
Specifically, whether the aluminum core integration quality of the target aluminum-plastic composite board is up to standard is judged, and the method further comprises: aluminum core integration quality evaluation coefficient of analysis target aluminum-plastic composite boardThe calculation formula is as follows: />Integrating the composite board with a preset composite board aluminum core to obtain a reasonable quality evaluation coefficient threshold value +.>Comparing, if->And (5) judging that the aluminum core integration quality of the target aluminum-plastic composite board meets the standard, and otherwise, judging that the aluminum core integration quality of the target aluminum-plastic composite board does not meet the standard.
According to the embodiment of the invention, the three-dimensional structure model of the inner aluminum core of the target aluminum-plastic composite board is constructed, and the egg-support type conical structure of the three-dimensional structure model is aimed at, so that the evaluation coefficients of the lamination degree between each egg-support structure of the aluminum core of the target aluminum-plastic composite board, the aluminum plate and the plastic plate are evaluated, the aluminum core integration quality evaluation coefficient of the target aluminum-plastic composite board is analyzed, the defect that the conventional method has insufficient or insufficient consideration on the layer is overcome, the support strength and the tight lamination degree of the aluminum core structure in the target aluminum-plastic composite board are effectively known, the production quality control process of the aluminum-plastic composite board is further optimized, the production efficiency is improved, and the production cost is reduced.
S4, detecting the adhesion quality of the composite board coating: and (3) respectively carrying out image acquisition on the surface coating of the target aluminum-plastic composite board under the same angle and different illumination conditions by using the high-definition camera for detecting the three areas, judging whether the coating adhesion quality of the target aluminum-plastic composite board meets the standard, if so, executing S5, otherwise, printing three-level unqualified labels on the target aluminum-plastic composite board and executing S6.
Specifically, the method for judging whether the coating adhesion quality of the target aluminum-plastic composite board meets the standard comprises the following steps: and recording each surface coating image of the target aluminum-plastic composite board acquired under the same angle and different illumination conditions as each appointed image, obtaining a coating integrated image through image fusion processing, and converting the coating integrated image into an RGB color space after preprocessing to obtain the intensity value of each pixel point in the coating integrated image in a R, G, B color channel.
Extracting a coating design color of the WEB cloud storage target aluminum-plastic composite board, analyzing an intensity value of a R, G, B color channel corresponding to the color, constructing a chromaticity three-dimensional coordinate system by taking R, G, B color channel intensity as a coordinate axis, obtaining coordinates of each pixel point in a coating integrated image and the coating design color, and calculating coordinate distances between each pixel point in the image and the coating design colorWherein->For coating the number of each pixel in the integrated image, < >>。
It should be noted that, the coordinate distance between each pixel point in the image and the designed color of the coating is calculated by using the Euclidean distance formula in the three-dimensional space.
Dividing the region of the coating integrated image to obtain each image subarea, and calculating the gray average value of each image subareaWherein->For the numbering of the sub-areas of the respective image>。
The gray average value of each image subregion is obtained by converting each image subregion into a gray image and calculating the average value of the gray values of each pixel point in each image subregion.
The coating injection quality evaluation coefficient of the analysis target aluminum-plastic composite board is calculated by the following formula:wherein->For the number of image subregions>And designing a coordinate distance limiting threshold value of the color for the pixel point in the preset image and the coating.
According to the embodiment of the invention, the difference between the spray color and the design color of the coating in the target aluminum-plastic composite board coating integrated image is analyzed in the form of the coordinate distance, the matching degree of the coating color and the design color is quantitatively evaluated, the color precision and consistency of the product are ensured, and the spray uniformity of the coating is carefully known by the gray average value deviation among all subareas in the target aluminum-plastic composite board coating integrated image, so that the spray quality of the coating is more accurately evaluated.
Specifically, the method for judging whether the coating adhesion quality of the target aluminum-plastic composite board meets the standard comprises the following steps: aiming at each appointed image, each suspected raised area and each suspected recessed area in each appointed image are obtained through the set pixel threshold range and the connected domain searching processing, each actual raised area and each actual recessed area of the target aluminum-plastic composite board surface coating are further screened out by utilizing the recessed shadow fluctuation characteristics and the raised high light fluctuation characteristics, the corresponding areas and the corresponding depths are obtained and are respectively recorded asWherein->For the number of the actual raised areas +.>，/>For the number of the actual recessed areas +.>The flatness of the surface coating of the target aluminum-plastic composite panel is analyzed, and the calculation formula is as follows: />Wherein->The surface coating area of the aluminum-plastic composite board is a preset target.
The method for acquiring each suspected convex region and each suspected concave region in each specified image comprises the following steps: and extracting an upper limit value and a lower limit value of a set pixel threshold range, if the gray value of a certain pixel point in the image is larger than the upper limit value of the set pixel threshold range, marking the pixel point as a convex pixel point, and if the gray value of the certain pixel point in the image is smaller than the lower limit value of the set pixel threshold range, marking the pixel point as a concave pixel point, so as to obtain each convex pixel point and each concave pixel point in each appointed image.
Selecting a convex pixel point in a specified image as a starting point to perform connectivity search, searching for a convex pixel point adjacent to the pixel point, marking the same region, repeatedly searching for adjacent pixel points until no convex pixel point is connected to a current region, marking the current region as a suspected convex region, continuing to repeat the operation until all the convex pixel points have the corresponding suspected convex regions, and dividing each suspected convex region by an image dividing technology to obtain each suspected convex region in the specified image, further obtaining each suspected convex region in each specified image, and similarly obtaining each suspected concave region in each specified image.
It should be further noted that, the areas of each actual protruding area and each actual recessed area of the surface coating of the target aluminum-plastic composite panel are obtained by obtaining the total number of pixels in the areas and converting according to a set proportional relationship, and the depths of each actual protruding area and each actual recessed area of the surface coating of the target aluminum-plastic composite panel can be obtained by calculating the relative height difference between the bottom of the area and the surrounding area.
Specifically, the screening process of each actual convex area and each actual concave area of the surface coating of the target aluminum-plastic composite plate is as follows: and acquiring a highlight value of each suspected convex region and a shadow value of each suspected concave region in each appointed image, taking the position of the region center unit pixel circle domain as a base point, screening each convex region and each concave region with the same position of the region center unit pixel circle domain in each appointed image, and respectively marking the convex region and the concave region as each preliminary selected convex region and each preliminary selected concave region.
The above-mentioned area center unit pixel circle field refers to a unit pixel circle field constructed by taking an area center point as a dot and taking a unit pixel value as a radius, and aims to better acquire a convex area and a concave area at the same position between each specified image.
And checking the highlight value of each primary selection convex area in each designated image and the shadow value of each primary selection concave area in each designated image, and obtaining the highlight fluctuation factor of each primary selection convex area and the shadow fluctuation factor of each primary selection concave area.
It should be noted that the highlight fluctuation factor and the shadow fluctuation factor are calculated by a standard deviation formula.
If the high-light-wave factor of a certain primary selected bulge area is smaller than the set value, the primary selected bulge area is indicated to be an actual bulge area, and then each actual bulge area of the surface coating of the target aluminum-plastic composite plate is obtained, and each actual concave area of the surface coating of the target aluminum-plastic composite plate is obtained in a similar manner.
According to the embodiment of the invention, by utilizing the concave shadow fluctuation characteristics and the convex high light fluctuation characteristics under different illumination conditions of the same shooting angle, each actual convex area and each actual concave area of the surface coating of the target aluminum-plastic composite plate are reasonably screened, so that the accuracy and scientificity of data analysis are ensured to a great extent, and further, the higher credibility of the data analysis result is ensured.
Specifically, whether the coating adhesion quality of the target aluminum-plastic composite board reaches the standard is judged, and the method further comprises the following steps: analysis target aluminum-plastic composite board coating adhesion quality standard coefficientThe calculation formula is as follows: />The adhesive quality evaluation coefficient of the composite board coating is reasonably threshold value +.>Comparing, if->And judging that the coating adhesion quality of the target aluminum-plastic composite plate reaches the standard, and otherwise, judging that the coating adhesion quality does not reach the standard. />
According to the embodiment of the invention, the coating spraying quality evaluation coefficient and the flatness of the surface coating of the target aluminum-plastic composite plate are analyzed, the coating adhesion quality evaluation coefficient of the target aluminum-plastic composite plate is comprehensively considered, each aspect of the coating can be accurately, comprehensively and deeply known, the attractiveness, the durability and the service life of the aluminum-plastic composite plate are ensured, and therefore, the requirements of various practical applications are met.
S5, conveying a qualified production area of the composite board: and transmitting the target aluminum-plastic composite plate to a production qualified area.
S6, conveying the unqualified areas of composite board production: and transmitting the target aluminum-plastic composite plate to a production failure area.
According to the embodiment of the invention, the first-stage, second-stage and third-stage unqualified labels are printed on the target aluminum-plastic composite board, so that unqualified products can be conveniently tracked and traced, the reasons for quality problems can be better analyzed, quality maintenance and control can be more quickly performed, and the quality control efficiency can be improved.
The foregoing is merely illustrative of the structures of this invention and various modifications, additions and substitutions for those skilled in the art of describing particular embodiments without departing from the structures of the invention or exceeding the scope of the invention as defined by the claims.
Claims (10)
1. The machine vision-based aluminum-plastic composite board production quality detection and analysis method is characterized by comprising the following steps of:
s1, conveying a composite board production quality detection area: transmitting the produced target aluminum-plastic composite board to a production quality detection area through a transmission belt, wherein the production quality detection area comprises a first detection area, a second detection area and a third detection area;
s2, detecting the quality of the basic design of the composite board: scanning edge line segments of the target aluminum-plastic composite board through a line scanning camera for detecting a first area, constructing a three-dimensional basic frame model of the target aluminum-plastic composite board, judging whether basic design quality of the target aluminum-plastic composite board meets the standard, if so, continuously transmitting the target aluminum-plastic composite board to a second detection area and executing S3, otherwise, printing a first-level unqualified label on the target aluminum-plastic composite board and executing S6;
s3, detecting the integration quality of the aluminum core of the composite board: scanning the inside of the target aluminum-plastic composite board through a laser scanning instrument in the second detection area, constructing an internal aluminum core three-dimensional structure model of the target aluminum-plastic composite board, judging whether the aluminum core integration quality of the target aluminum-plastic composite board meets the standard, if so, continuously transmitting the target aluminum-plastic composite board to the third detection area and executing S4, otherwise, printing a second-level unqualified label on the target aluminum-plastic composite board and executing S6;
s4, detecting the adhesion quality of the composite board coating: respectively carrying out image acquisition on the surface coating of the target aluminum-plastic composite board under different illumination conditions of the same angle by using a high-definition camera for detecting the three areas, judging whether the coating adhesion quality of the target aluminum-plastic composite board meets the standard, if so, executing S5, otherwise, printing three-level unqualified labels on the target aluminum-plastic composite board and executing S6;
s5, conveying a qualified production area of the composite board: transmitting the target aluminum-plastic composite plate to a production qualified area;
s6, conveying the unqualified areas of composite board production: and transmitting the target aluminum-plastic composite plate to a production failure area.
2. The machine vision-based aluminum-plastic composite panel production quality detection and analysis method according to claim 1, wherein the method comprises the following steps of: whether the basic design quality of the target aluminum-plastic composite board meets the standard or not is judged, and the method comprises the following steps: importing a three-dimensional basic frame model of a target aluminum-plastic composite board into software with a three-dimensional size analysis function, acquiring basic size parameters including length, width and height, comparing the basic size parameters with design size parameters of the target aluminum-plastic composite board stored in a WEB cloud, and obtaining size deviation values of the length, the width and the height of the target aluminum-plastic composite board, wherein the size deviation values are respectively recorded asCalculating the size design conformity of the target aluminum-plastic composite plate>，/>Wherein->The length, the width and the height of the target aluminum-plastic composite board in the design size parameters are as follows;
the three-dimensional basic frame model of the target aluminum-plastic composite board is provided with a set number of planes, each plane is regarded as a rectangle, two base edges and two high edges exist, a pair of base edges and high edges with adjacent relation in the planes are marked as adjacent groups of edges, a pair of base edges or high edges with opposite relation in the planes are marked as opposite groups of edges, the parallelism of each opposite group of edges and the perpendicularity of each adjacent group of edges in each plane of the target aluminum-plastic composite board are obtained and respectively marked asWherein->Numbering each plane of the target aluminum-plastic composite panel,，/>numbering the opposite edges in the plane, < >>，/>Numbering the adjacent groups of edges in the plane, < >>Calculating the basic cutting conformity of the target aluminum-plastic composite board>，Wherein->Is natural constant (18)>The number of the aluminum-plastic composite plates is the target number of the planes of the aluminum-plastic composite plates.
3. The machine vision-based aluminum-plastic composite panel production quality detection and analysis method as claimed in claim 2, wherein the method is characterized by comprising the following steps of: the method for obtaining the parallelism of each opposite group of edges and the perpendicularity of each adjacent group of edges in each plane of the target aluminum-plastic composite board comprises the following steps: acquiring the relative angles of each relative group of edges and each adjacent group of edges in each plane of the target aluminum-plastic composite board through an angle measuring tool in software with a three-dimensional size analysis functionBy the formula->Obtaining the parallelism of each opposite group edge in each plane of the target aluminum-plastic composite board, and obtaining the parallelism of each opposite group edge in each plane of the target aluminum-plastic composite board by the formula +.>And obtaining the perpendicularity of each adjacent group of edges in each plane of the target aluminum-plastic composite board.
4. The machine vision-based aluminum-plastic composite panel production quality detection and analysis method as claimed in claim 2, wherein the method is characterized by comprising the following steps of: whether the basic design quality of decision target aluminum-plastic composite panel reaches the standard still includes: calculating basic design quality evaluation coefficient of target aluminum-plastic composite board，/>Which is provided withMiddle->Respectively obtaining a weight ratio corresponding to the preset size design conformity and the basic cutting conformity, and reasonably threshold value of basic design quality evaluation coefficient and preset basic design quality evaluation coefficient of the target aluminum-plastic composite board>Comparing, if->And judging that the basic design quality of the target aluminum-plastic composite plate meets the standard, and otherwise, judging that the basic design quality of the target aluminum-plastic composite plate does not meet the standard.
5. The machine vision-based aluminum-plastic composite panel production quality detection and analysis method according to claim 1, wherein the method comprises the following steps of: whether the aluminum core integration quality of the target aluminum-plastic composite board meets the standard or not is judged, and the method comprises the following steps: extracting a standard internal aluminum core three-dimensional structure model of a target aluminum-plastic composite board stored in a WEB cloud, recognizing the aluminum core of the target aluminum-plastic composite board as an egg-supporting conical structure, and acquiring contact distances between left and right endpoints of each egg-supporting structure and an aluminum plate in the internal aluminum core three-dimensional structure model of the target aluminum-plastic composite board, wherein the contact distances are respectively recorded asWherein->Numbering the egg tray structure>Analyzing the fitting degree evaluation coefficient between each egg support structure of the target aluminum-plastic composite board and the aluminum plate +.>The calculation formula is as follows:wherein->Is a reasonable deviation threshold value of the contact distance between the left end point and the right end point of the preset egg tray structure and the aluminum plate, < +.>For a reasonable threshold value of the contact distance between a preset egg-shaped support structure end point and an aluminum plate, further calculating an overall fit degree evaluation coefficient between an aluminum core of the target aluminum-plastic composite plate and the aluminum plate +.>，Wherein->A reasonable threshold value of a coefficient is evaluated for the degree of fit between a preset aluminum core egg support structure and an aluminum plate, and the degree of fit is ∈10>The aluminum core of the aluminum-plastic composite board is the target +.>Evaluation coefficient of the degree of adhesion between the individual egg-carrier structure and the aluminum plate, < >>The number of egg trays is the number of egg tray structures;
obtaining the attaching distance between the bottom surface of each egg support structure and the plastic plate in the internal aluminum core three-dimensional structure model of the target aluminum-plastic composite plateAnalyzing an overall adhesion degree evaluation coefficient between an aluminum core and a plastic plate of a target aluminum-plastic composite plate +.>。
6. The machine vision-based aluminum-plastic composite panel production quality detection and analysis method according to claim 5, wherein the method comprises the following steps of: whether the aluminum core integration quality of the target aluminum-plastic composite board meets the standard or not is judged, and the method further comprises the following steps: aluminum core integration quality evaluation coefficient of analysis target aluminum-plastic composite boardThe calculation formula is as follows: />Integrating the composite board with a preset composite board aluminum core to obtain a reasonable quality evaluation coefficient threshold value +.>Comparing, if->And (5) judging that the aluminum core integration quality of the target aluminum-plastic composite board meets the standard, and otherwise, judging that the aluminum core integration quality of the target aluminum-plastic composite board does not meet the standard.
7. The machine vision-based aluminum-plastic composite panel production quality detection and analysis method according to claim 1, wherein the method comprises the following steps of: whether the coating adhesion quality of the target aluminum-plastic composite board reaches the standard or not is judged, and the method comprises the following steps: recording each surface coating image of the target aluminum-plastic composite board acquired under the same angle and different illumination conditions as each appointed image, obtaining a coating integrated image through image fusion processing, and converting the coating integrated image into an RGB color space after preprocessing to obtain the intensity value of each pixel point in the coating integrated image in a R, G, B color channel;
extracting a coating design color of the WEB cloud storage target aluminum-plastic composite board, analyzing an intensity value of a R, G, B color channel corresponding to the color, constructing a chromaticity three-dimensional coordinate system by taking R, G, B color channel intensity as a coordinate axis, obtaining coordinates of each pixel point in a coating integrated image and the coating design color, and calculating each pixel point and coating in the imageCoordinate distance of layer design colorWherein->For coating the number of each pixel in the integrated image, < >>；
Dividing the region of the coating integrated image to obtain each image subarea, and calculating the gray average value of each image subareaWherein->For the numbering of the sub-areas of the respective image>；
The coating injection quality evaluation coefficient of the analysis target aluminum-plastic composite board is calculated by the following formula:wherein->For the number of image subregions>And designing a coordinate distance limiting threshold value of the color for the pixel point in the preset image and the coating.
8. The machine vision-based aluminum-plastic composite panel production quality detection and analysis method as claimed in claim 7, wherein the method comprises the following steps of: whether the coating adhesion quality of the target aluminum-plastic composite board reaches the standard or not is judged, and the method comprises the following steps: for each specified image, through the set pixel threshold rangeThe method comprises the steps of obtaining each suspected raised area and each suspected recessed area in each appointed image through the search processing of the surrounding and connected areas, further screening each actual raised area and each actual recessed area of the surface coating of the target aluminum-plastic composite plate by utilizing the recessed shadow fluctuation characteristics and the raised high light fluctuation characteristics, obtaining the corresponding areas and depths of the actual raised areas and the actual recessed areas, and respectively marking asWherein->For the number of the actual raised areas +.>，/>For the number of the actual recessed areas +.>The flatness of the surface coating of the target aluminum-plastic composite panel is analyzed, and the calculation formula is as follows: />Wherein->The surface coating area of the aluminum-plastic composite board is a preset target.
9. The machine vision-based aluminum-plastic composite panel production quality detection and analysis method as claimed in claim 8, wherein the method is characterized by comprising the following steps of: the screening process of each actual convex area and each actual concave area of the surface coating of the target aluminum-plastic composite plate comprises the following steps: acquiring a highlight value of each suspected convex region and a shadow value of each suspected concave region in each appointed image, taking the position of a region center unit pixel circle domain as a base point, screening each convex region and each concave region with the same position of the region center unit pixel circle domain in each appointed image, and respectively marking the convex region and the concave region as each preliminary selected convex region and each preliminary selected concave region;
checking the highlight value of each primary selection convex area in each designated image and the shadow value of each primary selection concave area in each designated image, and obtaining the highlight fluctuation factor of each primary selection convex area and the shadow fluctuation factor of each primary selection concave area;
if the high-light-wave factor of a certain primary selected bulge area is smaller than the set value, the primary selected bulge area is indicated to be an actual bulge area, and then each actual bulge area of the surface coating of the target aluminum-plastic composite plate is obtained, and each actual concave area of the surface coating of the target aluminum-plastic composite plate is obtained in a similar manner.
10. The machine vision-based aluminum-plastic composite panel production quality detection and analysis method as claimed in claim 8, wherein the method is characterized by comprising the following steps of: whether the coating adhesion quality of the target aluminum-plastic composite board reaches the standard or not is judged, and the method further comprises the following steps: analysis target aluminum-plastic composite board coating adhesion quality standard coefficientThe calculation formula is as follows: />The adhesive quality evaluation coefficient of the composite board coating is reasonably threshold value +.>Comparing, if->And judging that the coating adhesion quality of the target aluminum-plastic composite plate reaches the standard, and otherwise, judging that the coating adhesion quality does not reach the standard.
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